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A survey on feature selection methods
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“This kind of initial feature pruning can improve out-of-sample model performance substantially (80).”
From Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System (2020) · cites this paper as [80]
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Metadata
- Authors
- Chandrashekar, G., & Sahin, F.
- Affiliations
- Rochester Institute of Technology (US)
- Corresponding author
- Chandrashekar, Girish
- ORCID
- Sahin, Ferat
- Venue
- Computers & Electrical Engineering
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 40
- Issue
- 1
- Pages
- 16-28
- ISSN
- 0045-7906 (ISSN-L)
- OpenAlex
- W2167101736
- Cited by
- 5,189
- References
- 92
- Citations by year
- 2026: 351 · 2025: 517 · 2024: 575 · 2023: 652 · 2022: 655 · 2021: 651 · 2020: 498 · 2019: 440 · 2018: 378 · 2017: 239 · 2016: 138 · 2015: 73 · 2014: 21
- FWCI
- 68.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Electrical Engineering (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- feature selection, high-dimensional data, filter methods, wrapper methods, embedded methods, dimensionality reduction, machine learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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